[AI Seminar] AI Seminar sponsored by Apple -- Chun-Liang Li -- October 10

Adams Wei Yu weiyu at cs.cmu.edu
Sat Oct 7 19:18:31 EDT 2017

Dear faculty and students,

We look forward to seeing you next Tuesday, October 10, at noon in NSH 1507
(unusual place) for AI Seminar sponsored by Apple. To learn more about the
seminar series, please visit the AI Seminar webpage

On Tuesday, Chun-Liang Li <http://www.cs.cmu.edu/~chunlial/> will give the
following talk:

Title: MMD GAN: Towards Deeper Understanding of Moment Matching Network


Generative moment matching network (GMMN) is a deep generative model that
differs from Generative Adversarial Network (GAN) by replacing the
discriminator in GAN with a two-sample test based on kernel maximum mean
discrepancy (MMD). Although some theoretical guarantees of MMD have been
studied, the empirical performance of GMMN is still not as competitive as
that of GAN on challenging and large benchmark datasets. The computational
efficiency of GMMN is also less desirable in comparison with GAN, partially
due to its requirement for a rather large batch size during the training.
In this paper, we propose to improve both the model expressiveness of GMMN
and its computational efficiency by introducing adversarial kernel learning
techniques, as the replacement of a fixed Gaussian kernel in the original
GMMN. The new approach combines the key ideas in both GMMN and GAN, hence
we name it MMD-GAN. The new distance measure in MMD-GAN is a meaningful
loss that enjoys the advantage of weak topology and can be optimized via
gradient descent with relatively small batch sizes. In our evaluation on
multiple benchmark datasets, including MNIST, CIFAR- 10, CelebA and LSUN,
the performance of MMD-GAN significantly outperforms GMMN, and is
competitive with other representative GAN works.
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